5 дней назад
Senior/Lead Big Data Engineer (Databricks + GCP)
Мэтч & Сопровод
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Описание вакансии
Текст:
TL;DR
Senior/Lead Big Data Engineer (Databricks + GCP): Building scalable batch and streaming data pipelines and cloud-native data platforms on GCP with an accent on Databricks, Apache Spark, Python, SQL, and modern data modeling. Focus on designing reliable lakehouse architectures, optimizing large-scale processing, and delivering data solutions from discovery through production deployment.
Location: Romania, Bulgaria, or Poland; remote or office work
Company
delivers engineering and technology solutions, including cloud-based data platforms and analytics systems.
What you will do
- Design, develop, and maintain scalable batch and streaming data pipelines.
- Build and optimize data processing solutions with Python, SQL, Java, Apache Spark, and Databricks.
- Create cloud-native data architectures using BigQuery, Dataflow, Cloud Composer, Pub/Sub, and Cloud Storage.
- Implement data transformation, modeling, and analytics engineering practices with dbt and Dataform.
- Collaborate with stakeholders, architects, and engineering teams to translate requirements into technical solutions.
- Support end-to-end delivery from proofs of concept and MVPs to production deployments and platform enhancements.
Requirements
- 5+ years of professional experience in Big Data or Data Engineering.
- Advanced Python and SQL skills for large-scale data processing and transformation.
- Hands-on experience with GCP, Apache Spark, Cloud Dataflow or Apache Beam, and Databricks lakehouse solutions.
- Experience with Apache Airflow or Cloud Composer, Kafka or Google Cloud Pub/Sub, BigQuery, dbt, and Dataform.
- Strong analytical, troubleshooting, problem-solving, and stakeholder communication skills.
- Upper-intermediate or higher English.
Culture & Benefits
- Remote or office-based work arrangement.
- Collaborative engineering environment with participation in technical design and architecture decisions.
- Opportunities to contribute across the full project lifecycle and to continuous platform improvement.
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